Olga N. Ivashova

The modernization of higher education opens up prospects for the use of artificial intelligence (AI) in the training of specialists in the field of information technology, including those for the agricultural sector. Interaction supported by generative content services, in particular neural networks for working with tables, has the potential to improve the quality of student training. The aim of the study is to identify the specific aspects of the use of neural networks for working with tables in the training of IT specialists to improve its quality. The leading approach is modeling situations related to solving complex problems and developing innovative solutions for data analysis and processing. At the stage of assessing the quality of training of IT specialists, the materials of the control work including 50 questions (open and closed types) are used. The experimental work involves 64 students of the Russian State Agrarian University named after K. A. Timiryazev, studying in the field of training 09.03.02 Information systems and technologies, specialization "Computer science and data mining". Scientific novelty: the potential of including generative services for working with tables in the training of information technology specialists is substantiated. The results present the ideas of a methodological approach aimed at strengthening the influence of the identified factors to improve the quality of student training: the gradual, practical integration of AI elements into educational activities for the creation, processing of information and subsequent data analysis; the use of neural networks to work with tables at the hypothesis testing stage, compliance with information security rules. Theoretical significance – the identified didactic capabilities of neural networks for working with tables are clarified in relation to the training of students who are able to develop innovative solutions for data analysis, processing and protection. Practical significance – the factors influencing the effectiveness of the inclusion of neural networks for working with tables in the training of highly qualified personnel in the field of information systems and technologies have been identified. The results obtained are the basis for improving the training program for IT specialists and agricultural engineers. In conclusion, the specific features of using neural networks to work with tables are formulated: creating conditions for understanding the importance of the profession; combining theory and practice of information interaction; informing students about the limitations of using AI; accounting for cybersecurity issues.

The need to study and apply the potential of network technologies to improve the general cultural and professional level becomes an important condition for the training engineers of a new generation. To realize this potential of computer devices and digital tools, highly qualified specialists need the skills to divide the task into components, identify similar elements, select the most important information and discard the irrelevant, write the algorithm. The authors examine the problem of justifying the effectiveness of network training for the development of skills that form the basis of computational thinking of technical specialists. The purpose of the study is to examine the opportunities of using a professionally–oriented network course for the development of computational thinking in engineers of a new generation. The scientific novelty lies in the fact that the potential of the distance learning course for the formation of computational skills of future professionals is substantiated. Theoretical significance – the didactic opportunities of network courses are revealed, taking into account the peculiarities of training specialists in engineering and technical areas. The study was conducted using the authors’ original course in the discipline "Computing Technology and Networks in the Industry" (registration certificate No. 24877 of 28.08.2021). The course is implemented by means of the Moodle platform tools. 68 bachelors in the area of training 23.03.01 "Technology of transport processes" were involved in the study – specialization: "Digital transport and logistics systems of road transport". To diagnose and assess the formation of computational thinking, the authors used original testing materials: 40 questions in accordance with the working program of the discipline. Pearson's χ2 (chi-square) test was used as a statistical processing method. When working with the materials of a network course, a new generation engineer performs a sequence of actions characteristic of computational thinking: analyzes the text of a professional-oriented task; decomposes the problem; compiles and implements the algorithm; performs its analysis and evaluation. Positive aspects of the professional-oriented network course application for the development of computational thinking of engineers are highlighted (for example, to gain experience in formulating a problem taking into account the uncertainty of the future, students analyze the corporate network, determine the subnet mask for different conditions, etc.). Options for the practical application of the study results are proposed: in the work of the All-Russian network project for variety testing "Malaya Timiryazevka," in the activities of the Center for Pre-University Training and the digital department of the academy.